James Gardner, Chief Technology Officer at the Department for Work and Pensions in the UK and author of the blog, Banker Vision, explains the key components of corporate innovation.  Gardner’s “tools of innovation” also are aligned with the fundamental building blocks of prediction and idea markets. 

The Tools of Innovation – excerpts from James Gardner’s BankerVision 
Our commentary in italics

A.M Mills, the author of Hell Bent on Success asks me to explain what I mean by the “tools of innovation”. It is possible to summarise, I think, because everything you need to know about doing innovation happens in four stages.

1. Futurecasting
The first is futurecasting. This is the process of working out what is likely to happen in the future so you can guide subsequent iterations of your innovation process. In the book, for example, I explain a specific futurecasting process based loosely on a scenario planning methodology, but anything that gets structured consideration of the future on the table is a good thing. Why is this important? Well, firstly, you can never ask a senior person for support on something new, especially if that new thing impacts current business or revenue, without rehearsal. They need time to think over consequences, and making them think about the future helps them do that. The second reason is that random innovation without a guide won’t always result in new things that solve the strategic problems of the firm. Out of the box thinking is all very well, but if you are not only out of the box, but out of the ballpark, it is usually not helpful.  

For example, GE has run imagination markets successfully for several years, providing a vehicle for leaders to think about the future in the context of other options. GE imagination markets resulted in higher quality ideas than traditional methods.

• 60% of ideas rated as high quality
• Gathered valuable ideas and engaged employees in a fun way

2. Ideation
Ideation is the process of collecting ideas and deciding how good they are relative to all the other ideas that you might have. The thing is, if you’re running a programme, you’ll likely have far more ideas than resources to execute them. So you have to have a way of deciding what you’re going to work on. Of course, if you’re still thinking that the answer to your innovation challenge is getting the good ideas, then you have some work to do. Ideas are everywhere, and usually all you need to do is find a good way of collecting them. Anyway, you’ll have more ideas than you know what to do with, so one of the main tools of innovation is a decent way to prioritise. Usually, people create various scoring systems to do this, but crowd based methods, such as voting and prediction markets work just as well. 

For example, Motorola launched an idea market in 2007, powered by Consensus Point, for  employees to prioritize thousands of ideas on a quarterly basis. Motorola realized the following benefits, in addition to effectively prioritizing ideas: 

• Increased number of new ideas that are pursued from 11% to 22%
• Decreased number of duplicate ideas by 50%

3. Innovate
The third stage is what I call the “innovate” stage, which is really all about the tools and processes you use to work out – in detail – the stuff that has to happen before an idea is actually fundable.  Anyway, to get to the crux of the matter here, you need to answer three questions. “Can we do this?”, which is technically, operationally, and environmentally, is the idea actually possible. “Should we do this?”, which is primarily economic, i.e. can we afford it, and if we can, will anyone want it?. And, finally, “When?”, which is mainly about the response of competitors or internal players. Answering all that means you have a case which is a candidate for funding and delivery. As you’d expect, there are lots of things you do for each of those questions to get to decent answers for as little investment as possible. 

For example, GE employees participating in the company’s “Imagination Market” trade or buy “ideas” based on how closely they believe an idea is aligned to the business objectives, how an idea compares to other alternatives, and if the idea is operationally feasible. Most often, the ideas represent new technology or new product ideas.

4. Execution
Once you have money, the final stage is execution, which is all about building the thing and getting it out in the market. Key tools here include all the things you need to do to win over users, prove you know what you’re doing from an operational perspective (remember, it’s innovation, so its new, so no one will have made it work before), and a ton of other things. But I think the most important thing is you don’t even get to the Execute stage until you’ve done a substantial amount of groundwork first.

Gardner’s “tools of innovation” are a useful guide to effective innovation management, and idea/innovation markets enable several steps in his recommended process.

Linda Rebrovick, CEO of Consensus Point, discussed effective uses of prediction markets, based on multiple years of supporting effective enterprise prediction markets in large companies and government organizations.  She explained that effective enterprise markets require 3 key components:  a proven and expert consultant, a solution that targets key business problems, and the right customer environment and implementation plan.  Rebrovick discussed several use cases highlighting customer examples across several industries and business problems. 

Click Here to Download Presentation (PDF)

Rami Levy, Distinguished Member of the Technical Staff, Technical Lead and Manager of Motorola’s Open Source Technologies Team, explained how Motorola added the TIX Market, powered by Consensus Point, in 2007 to address the challenges of increasing idea backlog and missed opportunities. Levy explained the evolution of the TIX Market and how, over time, the prediction market has streamlined the innovation process, yielding benefits of 55% decrease in disposition days and 40% increase in idea pursue rates. 

Click here to Download Presentation (PDF)

Robin Hanson, Chief Scientist of Consensus Point, discussed the advantages of prediction markets and how to develop effective markets to efficiently yield meaningful outcomes. 

Click here to Download Presentation (PDF)

San Francisco, CA (PRWEB) May 31, 2009 — The Prediction Market Clusters in collaboration with Aurora WDC, Consensus Point, University of Chicago Gleacher Executive Center and many others announces the Prediction Markets Summit and Collective Intelligence Cluster Friday 6 November 2009 in Chicago, Illinois, USA.

Prediction Markets Summit and Collective Intelligence Cluster The venue is the stunning University of Chicago Gleacher Executive Center in Chicago, Illinois, USA. 

Learn how prediction markets, social media and collective intelligence networks are fundamentally altering the enterprise landscape. New forecasting techniques and technologies are driving executive decision making, leading collaborative forecasting and optimizing supply chain management. Engage with experts in knowledge markets that are reshaping all practices of knowledge management (KM), advancing innovation and propelling enterprise knowledge ecologies of the future.

“There is not much that any of us do that is more important than telling the company what we know.” Jeff Severts, EVP, Best Buy

We are thrilled several key scholars and thought leaders will join your cluster including:
Robin Hanson, Professor, Economist, Polymath, George Mason University
George Neumann, George Daly Professor of Economics, University of Iowa

In 2004 James Surowiecki published his now-famous book, The Wisdom of Crowds: Why the Many Are Smarter Than the Few and How Collective Wisdom Shapes Business, Economies, Societies and Nations. For many this milestone introduced the era of collective intelligence for people, business, institutions, the environment and civil society.

“Thanks for organizing an extremely useful and informative workshop!” – Professor Tom Malone, MIT Center for Collective Intelligence

Testimonials

New ways to share, trade and aggregate information using Internet-based markets are exploding. These powerful Web 2.0 social media and network knowledge markets help companies, schools, governments and individuals to acquire and master ever-growing bodies of knowledge. These prediction market capabilities achieve mastery knowledge management (KM) and collective intelligence with stunning speed, efficiency and accuracy.

“Prediction markets are brutally honest and uncannily accurate.” – Geoffrey Colvin, Fortune Magazine

New collaborative market mechanisms and social innovations are driving collective intelligence networks. They resolve questions of science, technology, management, strategy, planning and policy far better than experts or management.

Collective intelligence inhabits the ceaseless flurry of self-correcting social exchanges, social networks and collective knowledge markets. They cover everything from politics and business plans to sports and new product features. Enormously potent, these social networks and markets generate new ideas and amass and refine knowledge and collective wisdom with blinding speed, low cost and accuracy.

Collective intelligence networks and knowledge markets have become commonplace in the enterprise. Top firms using prediction markets are Best Buy, Google, Microsoft, Eli Lilly, Abbott Laboratories and Yahoo! to name a few. Major analysts firms declare prediction markets critical to Enterprise 2.0 information and knowledge management portfolios.

“A company that can predict the future is a company that is going to win.” – Bernardo Huberman, PhD, Senior HP Fellow, HP Labs

Cluster sessions are focused, practical and conversational. They are for executives, directors, mangers, users and practitioners having immediate needs to apply collective intelligence networks and market mechanisms to advance enterprise business outcomes through mastery of collective wisdom.

Pricing and Availability

Registration for the Collective Intelligence Cluster is open and available now. All are welcome. The event participant tuition, including full-day experience, meals, refreshments, books, reception and materials is $399.00 Secure online event check-in and registration in advance required. Early-bird registration ($299.00) is open until 30 September 2009.

Prediction Markets Summit and Collective Intelligence Cluster

Collective Intelligence Cluster Sponsors

Sponsors of the Collective Intelligence Cluster are the world’s leading producers of prediction market software, services, exchanges and expertise. They supply continuous innovation in prediction markets and collective intelligence networks. They include Aurora WDC, ConsensusPoint, Mercury-RAC, Prediction Market Clusters and many others.

About Prediction Market Clusters

The Prediction Market Clusters, founded in 2004, are the global industry commons and open community for prediction markets and collective intelligence networks worldwide. The open, agnostic network is a focused collaboration of vendors, academia, traders, users, developers, markets, regulators and stakeholders. The goal is to provide awareness, diffusion, adoption and pull-through for enterprise, institutional and consumer prediction markets. The Prediction Markets Cluster is the worldwide Next Practices leadership network for collective intelligence networks practices, tools and theories. For more information, please visit Prediction Markets Cluster.

For more information, discounts and to sponsor the Collective Intelligence Cluster, please contact Jennifer Hulett, Tel: 714-458-3826 Fax: 714-572-3742, for details.

Brian Spears
GE Hitachi Nuclear Energy

Christina LaComb
John Interrante
Janet Barnett
Deniz Senturk-Dogonaksoy
GE Global Research Center

ABSTRACT
We present the outcome of an idea market run for one of GE Energy’s sub-businesses in July and August of 2006. GE Energy used this market to elicit and rank-order technology and product ideas from across the sub-business. In this experiment, we examine the behavior of traders that have submitted the ideas on the market and their influence on the market’s outcome. An idea’s submitter is clearly motivated to have his idea valued highly by the market, both by the funding given to the top idea as well as smaller prizes given to the top three ideas. In general, founders tended to buy their suggested ideas at prices above the volume-weighted-average price (VWAP) in significant volumes. We discuss the implications and mitigation strategies. A survey of market participants yielded mixed results regarding the market’s effectiveness at ranking ideas but very positive results regarding the quality of ideas proposed. 

Click here to read the full paper.

The Journal of Prediction Markets (2009) 3,1 17-39